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Why use placebos in clinical trials? A narrative review of the methodological literature
Abstract
Researchers have a number of different options for their choice of control or comparison intervention in randomized trials. We surveyed the methodological literature looking for reasons why a researcher might choose to administer a placebo (i.e., a mimic intervention) to control subjects. Two implicit assumptions were that the issue of placebo is pertinent only to drug trials and that the nonplacebo effect of a treatment is the "real" or "true" effect. Explicit reasons given in the literature for the use of placebos were facilitating blinding and controlling for the placebo effect. The importance of the latter was often inadequately argued. Reasons to avoid placebos in controlled trials, other than ethics and feasibility, are that placebos do not inform real decisions, and may interfere with accurate estimation of effect size and with nonspecific aspects of treatment. Placebo-controlled trials have high internal validity but may be difficult to apply to clinical practice; the situation is reversed for trials without placebo control.
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“Even though the placebo effect cannot be ruled out, as the active control group was not included [81]”
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Metadata
- Authors
- Vickers, A.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Corresponding author
- Vickers, A
- ORCID
- Vickers, A
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2000-02
- Volume
- 53
- Issue
- 2
- Pages
- 157-161
- ISSN
- 0895-4356 (ISSN-L)
- OpenAlex
- W1990079090
- Cited by
- 121
- References
- 44
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 4 · 2023: 3 · 2022: 3 · 2021: 4 · 2020: 8 · 2019: 8 · 2018: 2 · 2017: 6 · 2016: 3 · 2015: 4 · 2014: 3 · 2013: 2 · 2012: 6
- FWCI
- 1.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Neuroscience › Cognitive Neuroscience › Pain Management and Placebo Effect
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- placebo effect, blinding, internal validity, effect size estimation, treatment generalizability, randomized controlled trials
- MeSH terms
- Double-Blind Method, Humans, Placebos, Epidemiologic Research Design, Randomized Controlled Trials as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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